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2018 will be the tipping point for Artificial Intelligence (AI) in the transportation industry. It will be a year where AI becomes an essential tool with new understanding and recognition that it is critical to success. In our business and beyond, we’ve seen how influential this technology can be in changing business models and creating better transport solutions.

At Stage Intelligence, we’re seeing this become a reality. In 2017, we’ve seen tremendous momentum behind our business and growing demand for real AI solutions in transportation. We’re rolling out our AI-based Bike Share management solution in cities across the globe and changing the perception that Bike Share isn’t a viable, reliable transport option.

We are helping to accelerate transformation in transportation and utilising self-organising algorithms and elements of machine learning to simplify and empower Bike Share management.

2018: Challenges in AI

The future of transportation will be defined by AI. Research firm Gartner predicts that by 2020 almost every new software product will have AI technologies. In transportation, we are starting to see widespread application and development of AI technology that is being powered by the collection of data and use of algorithms.

That said, it is still a very young market with challenges ahead. I see three big challenges for AI in transportation:

Not All “AI” is the Same – Many businesses that say they use AI don’t actually have it deployed. It is a buzzword and many businesses are doing data visualisations or pretty interfaces but when you look under the hood there’s nothing there. Operators eager to benefit from AI don’t get what they paid for and won’t see the best of it.

Transportation Expertise and Focus – AI solutions need to address specific challenges. They need to be purpose built for transportation and developed by both experts in transportation and AI. Otherwise, you get generic solutions that solve generic problems rather than enabling real innovation and agility in transportation.

Nurturing AI – AI isn’t just about building solutions. It is about training it and nurturing it to deliver the results you want. It requires people, time, effort and a lot of data to continuously maintain and develop the technology. You don’t just flip a switch. It requires an expert experienced in developing and growing successful solutions.

As we see more AI-based solutions adopted, there will be a move towards quality and performance. Solutions that are based more on buzzwords than results will fade away.

In 2018, more people will understand the basics of AI and make better decisions about the solutions they deploy. That’s good for transportation and will accelerate its growth.

Building Better Bike Share Schemes

We’ve seen tremendous growth in our business over the past year. In 2017, we deployed our solutions in new corners of the world.

Our business development team led by Tom Nutley was out and about at events and meetings almost on a monthly basis. We’ve been successful in sharing our belief in automated rebalancing and using self-organising algorithms to build better Bike Share Schemes and that has led to trials and deployments around the world.

Our flagship BICO Bike Share Scheme management platform has been adopted and is supporting ridership growth in unique markets in the Americas and Europe. In 2017, We added greater functionality to BICO including a successful internationalisation process that helped us to better serve our partners abroad and dynamic replenishment values for greater predictive management of a scheme. Both have made it easier for operators to deploy and benefit from our solution.

We are also proud to have partnered with industry bodies to accelerate transformation in Bike Share Schemes. We are a member of the platform for European Bicycle Sharing & Systems (PEBSS), created by European Cyclist’s Federation (ECF). Our work with ECF and PEBSS highlights our commitment to growing a healthier cycling market for all.

In November, our usability data was shared around the world and is influencing conversation about how to create Bike Share Schemes that give riders an optimised experience. We are sharing our data and analytics to show what is possible in Bike Share when you take a new approach.

This Time Next Year

Throughout 2018, we will develop our AI technology for the shared mobility market, innovate for Bike Share operators and continue to roll our solutions around the world. It is an exciting time for our industry and we are ready to help our partners benefit from our solution and encourage the continued growth of Bike Share.

As cities around the globe continue to push towards cleaner and more sustainable transportation, we will see increased demand for user-friendly Biker Share. How cities and operators manage their schemes and support riders will define their success.

The tipping point in Bike Share will be seen when automated rebalancing becomes a critical part of any Bike Share operator’s conversations about growth. AI will at least be considered when discussing a path forward for schemes looking to grow. That’s a big step forward in an industry that is constantly changing.

There are a few things that I believe will define the Bike Share in 2018:

Growing Bike Share Schemes

As more Bike Shares use AI-based management solutions, riders will get a better experience and schemes will grow. It will enable faster decision making for bike distribution, ensuring that riders get bikes and docks where and when they need them. That drives growth and creates new efficiencies.

Move Towards Electric

We will see a greater push in electric cars, bikes and scooters in an effort to reduce emissions and drive down costs. We will see more Bike Share offering e-bikes and even further introduction of e-scooter sharing in cities around the world. With greater range and a larger, more diverse user base, schemes will need better management solutions to drive efficiency.

Mobility as a Service

We will see mobile phones play a greater role in traditional transportation. Mobility as Service (MaaS) showed its potential in 2017 and now MaaS will begin being rolled out in cities around the globe. It will streamline how we travel and deliver even more data about how we commute.

The End of the Free-For-All in Free Floating

The free-for-all in Free Floating Bike Share has to come to an end. Healthy markets do not tolerate massive oversupply and as we’ve seen in some cities in China it leads to failing schemes. Free Floating Bike Share Schemes need to be managed and follow policies set out by local governments to be successful. In 2018, we hope to see less mistakes made and a lesson to be learned.

All of these things will drive demand for AI-based solutions and the evolution of Bike Share Scheme management. Bike Share operations should be simpler to manage with better experiences for riders. In 2018, we will solve some of the challenges in transportation and deliver solutions that benefit cities, citizens and the environment. I see tremendous potential in our business and our industry. 2018 will be a phenomenal year for AI in transportation.

http://stageintelligence.co.uk/wp-content/uploads/2018/01/AI-City.jpg6001170stageintelligencehttp://stageintelligence.co.uk/wp-content/uploads/2017/05/Si-logo_long.pngstageintelligence2018-01-04 11:51:122018-01-04 11:51:472018: A Tipping Point for Artificial Intelligence in Transportation

Big data is changing how we experience cities and enabling us to live healthier, happier and more productive lives. As cities become smarter, big data is being used to reimagine transportation and how we get from A to B.

Every city is producing vast amounts of data every hour and every day. Increasingly this data is being captured and put to work creating new solutions, processes and experiences that improve how a city functions and is enjoyed by citizens.

Data can be used to improve, urban planning, health care, sustainability, transportation and just about every aspect of a city. The “smart” in Smart Cities is about taking this data and rapidly turning it into actionable insights.

According to IBM, a Smart City “makes optimal use of all the interconnected information available today to better understand and control its operations and optimise the use of limited resources”. It makes cities better places to live and enables the best use of what a city’s budgets, space, people and technologies.

By 2021, open and shared data has the potential to add $2.83 billion (10.4 Billion AED) to Dubai’s economy every year, according to a report produced by KPMG. That is a lasting and long-term impact on the city of Dubai and results from using data in a Smart City environment.

While Smart City deployments continue to grow, transportation is an area where we are already seeing the direct impact of data on how citizens live day-to-day. In modern cities, Bike Share Schemes have emerged as a healthy and efficient means of commuting and navigating a city.

These schemes are taking the Smart City concept and applying it to local challenges and succeeding in growing ridership and providing more citizens with healthy and efficient transportation.

It’s this citywide data that is at the heart of the three pillars of smarter public bike sharing system as set out in the Policy Framework for Smart Public-Use Bike Share by the Platform for European Bicycle Sharing & Systems (PEBSS). Data influences how rider priorities are met and how cities offer suitable conditions with sustainable technologies and innovation. Smart Cities support Bike Share Schemes by considering the people, infrastructure and technology elements.

To make data work for Bike Share Scheme operators, it needs to be collected, managed and analysed effectively. This is where Artificial Intelligence (AI) plays a crucial role. AI-based platform manages all available data to deliver valuable insights to operators. The illustration below highlights this.

Once a Bike Share Scheme has been launched and established, operators are often challenged to find ways to increase usability that can be simply managed. Convincing citizens to try and use Bike Share Schemes regularly depends on customer experience and the overall convenience of the scheme.

A Bike Share Scheme in a large metropolitan area could see that the majority of its active riders were dominated by those using the scheme for daily commutes and for social mobility. To continue the uptake within these segments of the market, the operator realised that it needed to solve usability issues and find an easier way to manage this.

It engaged Stage Intelligence to find a simple to manage solution for improving its schemes usability. Stage Intelligence’s BICO platform provides the Bike Share Scheme operator with real-time recommendations for bike distribution, ensuring that bikes and bike parking spaces are available when and where they are needed. Stage Intelligence solves availability challenges that limit Bike Share Scheme growth.

As technology continues to advance, cities don’t want to be left behind. Cities around the world are turning to Artificial Intelligence (AI) to facilitate and support the drive towards ‘Smart Cities’.

Organisations are realising the potential of cities in collecting and using valuable data to benefit its citizens. Big Data and AI are helping to drive new innovations and disruptions, especially within the transport sector.

We give a round-up of key advancements in AI technology with city environments. These articles show a future where AI could be at the heart of how we get from A to B.

AI Traffic Lights

AI Traffic lights, set to be implemented in Milton Keynes, UK for 2018, will aim to offer a more reactive solution to managing rush hour. Traffic lights at present run in sequence. The AI fitted lights will cover a 50 square mile area around busy zones to monitor traffic and lower congestion, making it safer for cyclists, buses and other vehicles.

The AI traffic lights are the first step to improve traffic by integrating with existing road signs and management systems. In the future, the traffic lights will be able to communicate with driverless cars to ensure they work effectively.

NVIDIA’s AI Security Camera –

According to NVIDIA, there are hundreds of millions of surveillance cameras around the globe, expected to reach approximately 1 billion by 2020. The amount of data that this creates is difficult to manage by human beings alone.

This is where AI technology can play a huge part. AI can be used to analyse vast amounts of data and accurately drive insights. Connected to the Cloud, AI-powered systems can track and monitor behaviour as well be a solution to a lot of city problems.

Connecting the Car Industry with AI

AI has transformed the transportation industry with new business models and ways of operating. The car industry is not any different. AI has bought new features and increased connectivity options while promising a future of driverless cars.

The advancements in AI are making vehicles safer, smarter and cost efficient for people. From major automotive brands to start-ups, AI is proving its value in improving operations and bringing innovations.

Launching a ‘Pop-up’ Bus

Citymapper’s CMX1, dubbed the ‘pop-up bus’, aims to offer bus routes that change dynamically according to traffic and demand. It analyses vast amounts of data to find where demand is and offer a bus route to meet that demand.

Public transport has remained unchanged over the years. Citymapper’s pop-up bus is a good example of how optimising your resources can find new efficiencies and benefits to operators, even in old traditional models.

At Stage, we use Artificial Intelligence to remove complexity in Bike Share Schemes. Through using real-time data, we can predict demand and manage supply to increase ridership and grow Bike Share schemes.

Artificial Intelligence (AI) is disrupting all kinds of industries and changing them for the better. While most discussions around AI are positive, there are still fears around AI’s impact on the job market.

In many cases, AI won’t replace workers but it will make them better at their jobs. It will enable workers to refocus their jobs around areas where a human touch can add value. The impact of AI is already being felt and we see it as not about phasing people out but finding smarter ways to work.

AI is enabling many types of jobs to become easier and more efficient. It permits extremely large quantities of data to be made accessible and useful for people to make faster and more precise decisions. While this can be seen as outsmarting human beings, it is actually enabling workers to manage and use more data with better results.

This means workers will be able to proactively manage situations based on extremely complex data patterns while businesses will be able to make larger and more targeted investments. It creates a new business environment that is different but isn’t simply about removing people from the workforce.

At the same time, AI is driving demand for new skills. We must be prepared to “up-skill and re-skill” according to the UK parliament.

At Stage Intelligence, we agree that education and training systems across the world should be developed and made more flexible. They should teach students about AI and the skills they need to accommodate to a life working with it. AI is not going away and as it becomes ever present within day-to-day life, specifically within the jobs market, it is important that we can all find a way to maximise the potential of AI in our businesses.

We believe that AI should be embraced as a technology that helps facilitate jobs and enhances our lives. At Stage Intelligence we use AI to create intelligent solutions to solve complex problems within logistics in Bike Share Schemes. Our AI is helping Bike Share Scheme operators to increase usability and ridership allowing its staff to focus on other core areas of the business. By embracing AI both individuals and technology can work together to make a better Bike Share Scheme.

It is important that we all find a way to embrace and work with AI. It should not be seen as a threat but rather as an opportunity. AI can improve the jobs market and evolve the ways of working to create greater efficiency, enhancing the lives of everyone.

What are your thoughts on the future role of AI within jobs? Share your ideas in a comment below.